Xu et al. [1]} was the pioneer who innovated attention mechanism into deep learning. Since then, a profusion of attention methods were designed mainly including channel attention [2]}, spatial attention [3]} and self-attention [4]}. Inspired by them, some works that incorporated attention mechanism into depth prediction have emerged. Chen et al. [5]} interpolated channel attention block into the encoder and spatial block into the decoder to avoid losing structural information. Xu et al. [6]} presented a fused CRF model guided by multi-scale attention. Choi et al. [7]} designed an affinity propagation unit to make the depth features guided by semantic attention map.
